• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.60-67
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• 2022

An Electro-Optical Tracking System (EOTS) is an electric optical system with EO/IR cameras, laser sensors, and an IMU. The EOTS calculates coordinates of targets, using attitude and acceleration measured by the IMU. In particular for an armed aircraft, the performance of the weapon system depends on how quickly and accurately it acquires the target coordinates. The IMU should be operated after alignment is complete, to meet the coordinate accuracy required by the weapon system so the initial stabilization time of the IMU should be reduced, by quickly measuring the attitude and acceleration. Alignment is the process of determining the initial attitude by resolving the attitude error of the IMU, and the IMU of mission equipment such as an airborne EOTS, uses velocity matching based on the velocity from GPS/INS for aircraft navigation. In this paper, a method is presented to improve the transfer alignment performance of the airborne EOTS, by maneuvering aircraft and the mission equipment. First, the performance factor of the alignment was identified, as a heading error through the velocity matching model and simulation results. Then acceleration maneuvers and attitude changes were necessary, to correct the error. As a result of flight tests applied to an EOTS on a OOO aircraft system, the transfer alignment performance was improved as the duration time was decreased, by more than five times when the aircraft accelerated by more than 0.2g and the EOTS was moving until 6.7deg/s.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.389-398
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• 2022

Many studies have been conducted to accurately predict the correlations between As and heavy metals content in contaminated soil and cultivated crops; however, due to the low correlation between the two, few clear results were obtained to date. This study aimed to create statistical models that predict the As content transferred from soil to polished rice, considering the physicochemical properties of the soil, as well as the total content and the single-extracted content of As in the soil. Predictive models were derived through regression analysis while sequentially classifying soil samples according to pH, soluble As content by single extraction, and organic matter content of the soil. The correlation coefficients between the As content in 80 polished rice and total As content and Mehlich soluble As content in the soil were low, 0.533 and 0.493, respectively. However, the models derived after sequential classification of the soil by pH, a ratio of total As content to Mehlich soluble As content, and organic matter content greatly increased the predictive power; ① 0.963 for 13 soils with a pH higher than 6.5, ② 0.849 for 15 soils with pH lower than 6.5 and a high ratio of As_Tot/As_Mehlich, ③ 0.935 for 30 soils with pH lower than 6.5, a high ratio of As_Tot/As_Mehlich, and organic matter content lower than 8.5%. The suggested prediction model of As transfer from soil to polished rice derived by soil classification may serve as a statistically significant methodology in establishing a rice cultivation standard for arsenic-contaminated soil.

• Journal of Environmental Impact Assessment
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• v.31 no.2
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• pp.83-94
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• 2022

In this study, DNN-based models were learned using air quality determination data for 2017, 2019, and 2020 provided by the National Measurement Network (Air Korea), and this models evaluated using data from 2016 and 2018. Based on Pearson correlation coefficient 0.2, four items (SO₂, CO, NO₂, PM₁₀) were initially modeled as independent variables. In order to improve the accuracy of prediction, monthly independent modeling was carried out. The error was calculated by RMSE (Root Mean Square Error) method, and the initial model of RMSE was 5.78, which was about 46% betterthan the national moving average modelresult (10.77). In addition, the performance improvement of the independent monthly model was observed in months other than November compared to the initial model. Therefore, this study confirms that DNN modeling was effective in predicting PM_2.5 concentrations based on air pollutants concentrations, and that the learning performance of the model could be improved by selecting additional independent variables.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.631-636
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• 2022

Alcohol content, which is an important standard for Takju, a traditional multiple parallel fermentation liquor called makgeolli, is a factor that can affect the flavor. For alcohol content analysis, the distillation/hydrometry technique is mainly used. In this study, we analyzed the alcohol content of 14 commercially available Takju by the distillation/hydrometry technique and the improved GC method, respectively, after verifying the reliability of improved GC method. The precision and accuracy of the GC method were satisfactory, and LOQ and LOD were evaluated as 0.5% and 0.1% of ethanol contents, respectively. Among the three Takju exceeding the labelled alcohol content ±1, one Takju was quantitated as alcohol content 9.9% (by GC method) and 10.1% (distillation/hydrometry technique) exceeding labelled 6.0%. It was within the analytical error range of alcohol content for other two Takju, where the alcohol contents were exceeded -1.1%. The average precision (%RSD) of 14 Takju analyzed by the distillation/hydrometry technique (36.2%) and the GC method (12.8%), confirming that the GC method was better than the other. The improved GC method was evaluated to be effective in managing and improving the alcohol content standard of Takju with the wide range of alcohol content.

• Smart Media Journal
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• v.11 no.11
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• pp.17-24
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• 2022

With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.26-31
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• 2023

For durability improvement of polymer electrolyte membrane fuel cell (PEMFC) polymer membrane, accelerated durability evaluation methods that can evaluate durability in a short time have been researched and developed. However, the lifespan of fuel cells for large commercial vehicles such as trucks and buses is more than three times that of passenger cars, and the chemical accelerated stress test (AST) time is also longer, reaching 1,500 hours or more. Therefore, in this study, as a method to evaluate the chemical durability of a membrane within a short time, it was examined whether the durability could be predicted by the pristine membrane characteristics. Hydrogen crossover current density (HCCD) and short resistance (SR) were estimated as initial characteristics, and AST time was predicted through the Fenton experiment, which was possible as an out-of-cell experiment for 3 hours. As the HCCD and fluoride ion emission concentration increased, the AST time tended to be linearly shortened, but there was a deviation (R² ≒0.65). When the SR decreased, the AST time showed a linear increase, and the accuracy was high (R² =0.93), so the AST time could be predicted with the initial SR of the membrane.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Journal of the Korean Geotechnical Society
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• v.24 no.10
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• pp.83-91
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• 2008

Previous settlement prediction methods based on settlement monitoring were developed under instantaneous loading condition and have restriction to be applied to soft ground under ramp loading condition. In this study, settlement prediction method under ramp loading was developed. New settlement prediction method under ramp loading considered influence factors of consolidation settlement such as thickness of clayed layer, quantity of surcharge load and preconsolidation pressure, etc. Geometrical correction method based on hyperbolic method (1991) and correction method based on probability theory were applied to increase accuracy of settlement prediction using field monitoring data after ramp loading. Large consolidation tests for ideally controlled one dimensional consolidation under ramp loading condition were performed and the settlement behavior was predicted based on the monitoring data. New prediction method yielded good result of entire settlement behavior by using data during an early stage of ramp load. Additionally, new prediction method offered better settlement prediction which had final settlement prediction in close proximity and low RMSE(Root Mean Square Error) than previous method such as hyperbolic method did.

• Korean Journal of Animal Reproduction
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• v.9 no.2
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• pp.133-139
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• 1985

An immunoassay may be defined as an analytical procedure involving the competitive reaction between a limiting concentration of specific antibody and two populations of antigen, one of which is labelled or immobillized. The advent of immunoassay has revolutionised our knowledge of reproductive physiology and the practice of veterinary and clinical medicine. Radioimmunoassay (RIA) was the first of these methods to be developed, which meausred the analyte with good sensitivity, accuracy and precision (1,2). The essential components of RIA are:-(i) a limited concentration of antibodies, (ii) a reference preparation, and (iii) an antigen labelled with a radioisotope (usually tritium or iodine-125). Most procedures invelove isolating the antibody-bound fraction and measuring the amount of labelled antigen. Good facilities are available for scintilltion counting, data reduction nd statistical analysis. RIA is undergoing refinement through:-(i) the introduction of new techniques to separate the antibody-bound and free fractions which minimize the misclassification of labelled antigen into these compartments, and the amount of non-specfic binding. (3), (ii) the development of non-extration for the measurement of haptens (4), (iii) the determination of a, pp.rent free (i.e. non-protein bound) analytes (5), and (iv) the use of monoclonal antibodies(6). In 1968, Miles and Hales introduced in important new type of immunoassay which they termed immunora-diometric assay (IRMA) based on t도 use of isotopically labelled specific antibodies(7) in a move from limited to excess reagent systems. The concept of two-site IRMAs (with a capture antibody on a solid-phase, and a second labelled antibody to a different antigenic determinant of the analyte) has enabled the development of more sensitive and less-time consuming methods for the measurement of protein hormones ovar wide concentration of analyte (8). The increasing use of isotopic methos for diverse a, pp.ications has exposed several problems. For example, the radioactive half-life and radiolysis of the labelled reagent limits assay sensitivity and imposes a time limit on the usefulness of a kit. In addition, the potential health hazards associated with the use and disposal of radioactive cmpounds and the solvents and photofluors necessary for liquid scientillation counting are incompatable with the development of extra-laboratory tests. To date, the most practical alternative labels to radioisotopes, for the measurement of analytes in a concentration > 1 ng/ml, are erythrocytes, polystyrene particiles, gold sols, dyes and enzymes or cofactors with a visual or colorimetric end-point(9). Increased sensitivity to<1 pg/ml may be obtained with fluorescent and chemiluminescent labels, or enzymes with a fluorometric, chemiluminometric or bioluminometric end-point. The sensitivity of any immunoassay or immunometric assay depends on the affinity of the antibody-antigen reaction, the specific activity of the label, the precision with which the reagents are manipulated and the nonspecific background signal (10). The sensitivity of a limited reagent system for the measurement of haptens or proteins is mainly dependent upon the affinity of the antibodies and the smalleest amount of reagent that may be manipulated. Consequently, it is difficult in practice to improve on the sensitivity obtained with iodine-125 as the label. Conversely, with excess reagent systems for the measurement of proteins it is theoretically possible to increase assay sensitivity at least 1000 fold with alternative luminescent labels. To date, a 10-fold improvement has been achieved, and attempts are being made to reduce the influence of other variables on the specific signal from the immunoreaction.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.131-146
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• 2023

Smart card data is widely used in the public transportation field. Despite the inevitability of various errors occur during the data collection and storage; however, smart card data errors have not been extensively studied. This paper investigates inherent errors in boarding and alighting station information in smart card data. A comparison smart card data and bus boarding and alighting survey data for the same time frame shows that boarding station names differ by 6.2% between the two data sets. This indicates that the error rate of smart card data is 6.2% in terms of boarding station information, given that bus boarding and alighting survey data can be considered as ground truth. This paper propose 6-step algorithm for correcting errors in smart card boarding station information, linking them to corresponding information in Bus Information System(BIS) Data. Comparing BIS data and bus boarding and alighting survey data for the same time frame reveals that boarding station names correspond by 98.3% between the two data sets, indicating that BIS data can be used as reliable reference for ground truth. To evaluate its performance, applying the 6-step algorithm proposed in this paper to smart card data set shows that the error rate of boarding station information is reduced from 6.2% to 1.0%, resulting in a 5.2%p improvement in the accuracy of smart card data. It is expected that the proposed algorithm will enhance the process of adjusting bus routes and making decisions related to public transportation infrastructure investments.